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BRIEF RESEARCH REPORT article

Front. Artif. Intell.

Sec. Machine Learning and Artificial Intelligence

The Association Between National Culture and AI Readiness: A Cross-National Study

Provisionally accepted
Kumiko  KomatsuKumiko Komatsu*Nina  ŽdanovičNina ŽdanovičMasaki  YamabeMasaki YamabeHiroyoshi  IwataHiroyoshi IwataMisa  IwamotoMisa IwamotoShutaro  TakedaShutaro Takeda
  • Keio University, Hiyoshi Campus, Yokohama, Japan

The final, formatted version of the article will be published soon.

While the adoption of Artificial Intelligence (AI) is advancing globally, its pace varies significantly across nations. This study statistically examines the associations between Hofstede's cultural dimensions and national-level AI readiness. A correlation analysis was conducted using data from the Oxford Insights' "Government AI Readiness Index 2024" and Hofstede's cultural dimension scores. The findings reveal that Individualism and Long-Term Orientation have a significant positive correlation with AI readiness, whereas Power Distance and Uncertainty Avoidance show a significant negative correlation. Conversely, Masculinity and Indulgence did not have a statistically significant relationship. These results suggest that national cultural characteristics are associated with differences in the adoption of advanced technologies such as AI. To contextualize the statistics, we include an illustrative, non-causal comparison of Japan, the United States, and Singapore.

Keywords: artificial intelligence, cross-cultural studies, Hofstede's cultural dimensions, national culture, Technology Adoption

Received: 20 Oct 2025; Accepted: 26 Jan 2026.

Copyright: © 2026 Komatsu, Ždanovič, Yamabe, Iwata, Iwamoto and Takeda. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Kumiko Komatsu

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